Data Engineering Weekly

MAY 16, 2023

It involves thorough checks and balances, including data validation, error detection, and possibly manual review. Data Testing vs. We call this pattern as WAP [Write-Audit-Publish] Pattern. In the 'Write' stage, we capture the computed data in a log or a staging area. Now, Why is Data Quality Expensive?

Engineering 111

Engineering Kafka Data Pipeline Data Warehouse 111

Towards Data Science

JULY 8, 2024

Williams on Unsplash Data pre-processing is one of the major steps in any Machine Learning pipeline. Before going further into Data Transformation, Data Validation is the first step of the production pipeline process, which has been covered in my article Validating Data in a Production Pipeline: The TFX Way.

Data Preparation 70

Data Preparation Datasets Metadata Data Ingestion 70

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Smart DwH Mover helps in accelerating data warehouse migration.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

RandomTrees

SEPTEMBER 6, 2020

The architecture is three layered: Database Storage: Snowflake has a mechanism to reorganize the data into its internal optimized, compressed and columnar format and stores this optimized data in cloud storage. This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Data Engineering Weekly

OCTOBER 30, 2022

link] ABN AMRO: Building a scalable metadata-driven data ingestion framework Data ingestion is a heterogenous system with multiple sources with its data format, scheduling & data validation requirements.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52